Model predictive control for discrete-event and hybrid systems
نویسنده
چکیده
Model predictive control (MPC) is a very popular controller design method in the process industry. A key advantage of MPC is that it can accommodate constraints on the inputs and outputs. Usually MPC uses linear or nonlinear discrete-time models. In this paper we give an overview of some results in connection with model predictive control (MPC) approaches for some tractable classes of discrete-event systems and hybrid systems. In general the resulting optimization problems are nonlinear and nonconvex. However, for some classes tractable solution methods exist. In particular, we discuss MPC for max-plus-linear systems, for mixed logical dynamical systems, and for continuous piecewise-affine systems.
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